publications

2026

1. ICML

   Foundation Models for Sparse, Multi-Relational Risk Prediction in Global Supply Chains

   Ruohong Li, George Pu, James Nordlund, and 3 more authors

   In Proceedings of the 2nd ICML Workshop on Foundation Models for Structured Data, Jul 2026

   Bib HTML PDF

   @inproceedings{li2026foundation,
     title = {Foundation Models for Sparse, Multi-Relational Risk Prediction in Global Supply Chains},
     author = {Li, Ruohong and Pu, George and Nordlund, James and D'Acunto, Salvatore and Visconti, Liz and Meiyappan, Prasanth},
     booktitle = {Proceedings of the 2nd ICML Workshop on Foundation Models for Structured Data},
     year = {2026},
     month = jul,
   }

2021

1. WSC

   Seeing through walls: real-time digital twin modeling of indoor spaces

   George Pu, Paul Wei, Amanda Aribe, and 4 more authors

   In Proceedings of the Winter Simulation Conference, Dec 2021

   Bib HTML PDF

   

   @inproceedings{pu2021seeing,
     title = {Seeing through walls: real-time digital twin modeling of indoor spaces},
     author = {Pu, George and Wei, Paul and Aribe, Amanda and Boultinghouse, James and Dinh, Nhi and Xu, Fang and Du, Jing},
     booktitle = {Proceedings of the Winter Simulation Conference},
     pages = {1--10},
     year = {2021},
     month = dec,
   }

2. ArXiv

   Server averaging for federated learning

   George Pu, Yanlin Zhou, Dapeng Wu, and 1 more author

   arXiv preprint arXiv:2103.11619, Mar 2021

   arXiv Bib PDF

   

   @article{pu2021server,
     title = {Server averaging for federated learning},
     author = {Pu, George and Zhou, Yanlin and Wu, Dapeng and Li, Xiaolin},
     journal = {arXiv preprint arXiv:2103.11619},
     year = {2021},
     month = mar,
   }

2020

1. NeurIPS

   Communication-efficient federated learning via dataset distillation

   Yanlin Zhou^*, George Pu^*, Xiyao Ma, and 2 more authors

   In NeurIPS Workshop on Scalability, Privacy, and Security in Federated Learning (SpicyFL), Dec 2020

   Bib PDF

   @inproceedings{zhou2020communication,
     title = {Communication-efficient federated learning via dataset distillation},
     author = {Zhou, Yanlin and Pu, George and Ma, Xiyao and Li, Xiaolin and Wu, Dapeng},
     booktitle = {NeurIPS Workshop on Scalability, Privacy, and Security in Federated Learning (SpicyFL)},
     year = {2020},
     month = dec,
   }

2. ArXiv

   Distilled one-shot federated learning

   Yanlin Zhou^*, George Pu^*, Xiyao Ma, and 2 more authors

   arXiv preprint arXiv:2009.07999, Sep 2020

   arXiv Bib PDF

   

   @article{zhou2020distilled,
     title = {Distilled one-shot federated learning},
     author = {Zhou, Yanlin and Pu, George and Ma, Xiyao and Li, Xiaolin and Wu, Dapeng},
     journal = {arXiv preprint arXiv:2009.07999},
     year = {2020},
     month = sep,
   }

2019

1. IROS

   Adaptive leader-follower formation control and obstacle avoidance via deep reinforcement learning

   Yanlin Zhou^*, Fan Lu^*, George Pu^*, and 4 more authors

   In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nov 2019

   arXiv Bib HTML PDF

   

   @inproceedings{zhou2019adaptive,
     title = {Adaptive leader-follower formation control and obstacle avoidance via deep reinforcement learning},
     author = {Zhou, Yanlin and Lu, Fan and Pu, George and Ma, Xiyao and Sun, Runhan and Chen, Hsi-Yuan and Li, Xiaolin},
     booktitle = {2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
     pages = {4273--4280},
     year = {2019},
     month = nov,
     organization = {IEEE},
   }